Thinking, Fast and Slow

Availability
There are situations in which people assess the frequency of a class or the
probability of an event by the ease with which instances or occurrences
can be brought to mind. For example, one may assess the risk of heart
attack among middle-aged people by recalling such occurrences a
[occpunishmentmong one’s acquaintances. Similarly, one may evaluate
the probability that a given business venture will fail by imagining various
difficulties it could encounter. This judgmental heuristic is called availability.
Availability is a useful clue for assessing frequency or probability, because
instances of large classes are usually recalled better and faster than
instances of less frequent classes. However, availability is affected by
factors other than frequency and probability. Consequently, the reliance on
availability leads to predictable biases, some of which are illustrated
below.
Biases due to the retrievability of instances. When the size of a class is
judged by the availability of its instances, a class whose instances are
easily retrieved will appear more numerous than a class of equal frequency
whose instances are less retrievable. In an elementary demonstration of
this effect, subjects heard a list of well-known personalities of both sexes
and were subsequently asked to judge whether the list contained more
names of men than of women. Different lists were presented to different
groups of subjects. In some of the lists the men were relatively more
famous than the women, and in others the women were relatively more
famous than the men. In each of the lists, the subjects erroneously judged
that the class (sex) that had the more famous personalities was the more
numerous.
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In addition to familiarity, there are other factors, such as salience, which
affect the retrievability of instances. For example, the impact of seeing a
house burning on the subjective probability of such accidents is probably
greater than the impact of reading about a fire in the local paper.
Furthermore, recent occurrences are likely to be relatively more available

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than earlier occurrences. It is a common experience that the subjective
probability of traffic accidents rises temporarily when one sees a car
overturned by the side of the road.
Biases due to the effectiveness of a search set. Suppose one samples
a word (of three letters or more) at random from an English text. Is it more
likely that the word starts with 
r or that r is the third letter? People approach
this problem by recalling words that begin with 
r (road) and words that have
r in the third position (car) and assess the relative frequency by the ease
with which words of the two types come to mind. Because it is much easier
to search for words by their first letter than by their third letter, most people
judge words that begin with a given consonant to be more numerous than
words in which the same consonant appears in the third position. They do
so even for consonants, such as 
r or k, that are more frequent in the third
position than in the first.
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Different tasks elicit different search sets. For example, suppose you
are asked to rate the frequency with which abstract words (
thought, love)
and concrete words (
door, water) appear in written English. A natural way
to answer this question is to search for contexts in which the word could
appear. It seems easier to think of contexts in which an abstract concept is
mentioned (love in love stories) than to think of contexts in which a
concrete word (such as 
door) is mentioned. If the frequency of words is
judged by the availability of the contexts in which they appear, abstract
words will be judged as relatively more numerous than concrete words.
This bias has been observed in a recent study
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which showed that the
judged frequency of occurrence of abstract words was much higher than
that of concrete words, equated in objective frequency. Abstract words
were also judged to appear in a much greater variety of contexts than
concrete words.